- New version of RAG_SPECIALIST and RAG_AGENT, including definition of conversation_purpose and response_depth.

eveai_chat_workers/definitions/conversation_purpose/conversation_purpose_v1_0.py

@@ -0,0 +1,30 @@
+CONVERSATION_PURPOSE = [
+    {
+        "name": "Informative",
+        "description": "Focus on sharing facts, explanations, or instructions.",
+        "when_to_use": "User seeks knowledge, clarification, or guidance."
+    },
+    {
+        "name": "Persuasive",
+        "description": "Aim to convince, motivate, or drive action. Highlights benefits and calls to action.",
+        "when_to_use": "Sales, marketing, or when encouraging the user to take a specific step."
+    },
+    {
+        "name": "Supportive",
+        "description": "Empathetic, solution-oriented, and reassuring. Prioritizes the user's needs and emotions.",
+        "when_to_use": "Customer support, healthcare, or emotionally sensitive situations."
+    },
+    {
+        "name": "Collaborative",
+        "description": "Encourages dialogue, brainstorming, and co-creation. Invites user input and ideas.",
+        "when_to_use": "Teamwork, creative processes, or open-ended discussions."
+    }
+]
+
+def get_conversation_purpose_context(conversation_purpose:str) -> str:
+  selected_conversation_purpose = next(
+    (item for item in CONVERSATION_PURPOSE if item["name"] == conversation_purpose),
+    None
+  )
+  conversation_purpose_context = f"{selected_conversation_purpose['description']}"
+  return conversation_purpose_context